聊城大学学报（自然科学版）2024，Vol.37Issue(4)：33-42,10.DOI:10.19728/j.issn1672-6634.2023110009
基于预定义时间收敛的容噪零化神经网络求解时变Sylvester方程
Predefined-Time Convergence-Based Noise-Tolerant Zeroing Neural Networks for Solving the Time-Varying Sylvester Equation
摘要
Abstract
Sylvester equations are often used in mathematics and control theory,and zeroing neural net-works(ZNN)are very effective at solving such time-varying equations.The convergence of ZNN is stud-ied,and a new activation function is designed based on a predefined time stability theorem,and a new ZNN model for solving time-varying Sylvester equations is obtained.This model is called a predefined Time Convergent zeroized neural network(PTZNN)model.Compared with the previous ZNN model,the proposed model improves the convergence speed to reach the predefined time convergence and further im-proves the noise tolerance.Then the simulation results show that the model is better than the known mod-el in solving the time-varying Sylvester equation.关键词
零化神经网络/容噪声能力/预定义时间收敛/Sylvester方程Key words
zeroing neural network/noise-tolerant capacity/predefined-time convergence/Sylvester equa-tion分类
信息技术与安全科学引用本文复制引用
岳远达,宓玲,陈川..基于预定义时间收敛的容噪零化神经网络求解时变Sylvester方程[J].聊城大学学报（自然科学版）,2024,37(4):33-42,10.基金项目
国家重点研发计划课题(2023YFB3107303) （2023YFB3107303）
山东省自然科学基金项目(ZR2021MF090) （ZR2021MF090）
山东省科技型中小企业创新能力提升工程项目(2023TSGC0197)资助 （2023TSGC0197）
